The world is currently experiencing COVID-19, one of the worst pandemics that have happened in this century, affecting 10.7 million people worldwide. It has caused massive growth in the number of employees working from home. However, employees have minimal cybersecurity resources unlike organizations with security teams protecting them against attacks. Hence, cybersecurity plays an important role as users can be easily targeted by cybercriminals. This paper examines how cyberattacks have increased during this pandemic and shows how greatly they have affected health organizations, individuals and social networking applications. Results of the attacks include data breaches, false announcements and operations being disrupted. Attacks occurring during this pandemic and how they were handled are also critically discussed. The existing contributions do touch on related attacks but do not provide in-depth solutions regarding the issues. Even though there are many works and findings that were done previously, technology is ever evolving. Therefore, we need to be well versed with current and future issues and provide the latest mechanisms to prevent cybersecurity threats from occurring. On our share, we intend to present our findings on the challenges being faced by the population and its increasing threats as well as presenting unique solutions that can help organizations or related persons understand or spread awareness on the importance of cybersecurity. Through the research performed in this paper, it is found that there are many ways these issues can be alleviated. However, the issue is that there is significant lack of action and investment in terms of actual implementation and application of the available solutions.

The rapid growth of network services, Internet of Things devices and online users on the Internet have led to an increase in the amount of data transmitted daily. As more and more information is stored and transmitted on the Internet, cybercriminals are trying to gain access to the information to achieve their goals, whether it is to sell it on the dark web or for other malicious intent. Through thorough literature study relating to the causes and issues that are brought from the security and privacy segment of wireless networks, it is observed that there are various factors that can cause the networks to be an insecure; especially factors that revolve around cybercriminals with their growing expertise and the lack of preparation and efforts to combat them by relevant bodies. The aim of this paper is to showcase major and frequent security as well as privacy issues in wireless networks along with specialized solutions that can assist the related organizations or the public to fathom how great of an impact these challenges can bring if every related stakeholder took a step in reducing them. Through this paper it is discovered that there are many ways these challenges can be mitigated, however, the lack of implementation of privacy and security solutions is still largely present due to the absence of practical application of these solutions by responsible parties in real world scenarios.

This study explores the impact of multi-user interaction, group work, and simulations within virtual worlds on language learning and the development of intergroup empathy. Two distinct research projects were conducted, involving a total of 241 participants aged 19-45. The language learning study engaged 116 participants in diverse interactive experiences, while the intercultural study had 125 participants collaborating in multicultural groups and participating in perspective-taking simulations. Both studies employed qualitative data collection methods, including surveys, interviews, and observations. The findings suggest that the combination of networking strategies, collaborative learning, and simulations within virtual worlds contributes to improvements in learners' language proficiency, confidence, and empathy towards diverse social groups. Participants reported increased motivation and engagement, attributed to the immersive and interactive nature of the virtual environments. The studies highlight the importance of collaboration and reflection in facilitating language acquisition and intercultural understanding. Technical challenges were identified as potential barriers to implementation. The results demonstrate the potential of virtual worlds to enhance language education and foster empathy in diverse societies, offering valuable insights for educators and researchers. However, the findings may be limited by the specific contexts and sample sizes of the studies, warranting further research to explore the generalizability and long-term impact of virtual world interventions. not exaggerate the main conclusions.

We present the design and overall development of an eight degrees of freedom (DOF) based Bioinspired Quadruped Robot (BiQR). The robot is designed with a skeleton made of cedar wood. The wooden skeleton is based on exploring the potential of cedar wood to be a choice for legged robots’ design. With a total weight of 1.19 kg, the robot uses eight servo motors that run the position control. Relying on the inverse kinematics, the control design enables the robot to perform the walk gait-based locomotion in a controlled environment. The robot has two main aspects: 1) the initial wooden skeleton development of the robot showing it to be an acceptable choice for robot design, 2) the robot’s applicability as a low-cost legged platform to test the locomotion in a laboratory or a classroom setting.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

This research focuses on the development of an automated medication delivery system using Unmanned Aerial Vehicle (UAV) Technology and the Internet of Things (IoT) to support telemedicine and community welfare in the KLU region. The system is designed to improve the quality of medical services and medication management for the community in the area. One of the main challenges faced is how the KLU community responds and accepts automatic medication delivery using UAVs and IoT. To overcome this challenge, this research suggests providing education and training to the community about the benefits and usage of the system, as well as displaying a working simulation of the system to the community.

Abstract: Background: Recently, cardiorespiratory fitness (CRF) has been postulated as an adverse health outcome related to poor sleep quality. However, studies investigating the relationship between CRF with subjective sleep quality index are scarce. Thus, the current study aimed to investigate the association between CRF and Pittsburgh sleep quality index (PSQI) in apparently healthy people. The secondary aim was to investigate the association between reported physical activities (PA) and PSQI. Methods: 33 apparently healthy male participants volunteered to participate. CRF (VO2 peak) was measured via cardiopulmonary exercise testing on a treadmill. A short form of the International physical activity questionnaire (IPAQ) was used to measure PA, and PSQI was used for sleep quality index. Results: There was no correlation between CRF and PSQI total score or any component of the PSQI. Also, there was no correlation between IPAQ and PSQI total score. Categorical data analysis of the two questionnaires revealed that 45.5% of the participants reported low physical activity and poor sleep quality. Conclusions: There was no association between CRF, reported PA with subjective sleep quality index. The use of objective tools for assessing the quality and quantity of sleep should be recommended for future studies as it may clarify the association between CRF and sleep quality.

In this study, we investigate the performance of the saddlepoint approximation of the probability mass function and the cumulative distribution function for the weighted sum of independent Poisson random variables. The goal is to approximate the hazard rate function for this complicated model. The better performance of this method is shown by numerical simulations and comparison with a performance of other approximation methods.

The development of synthetic biology has enabled us to make massive progress on biotechnology and to approach research questions from a brand new perspective. In particular, the design and study of gene regulatory networks in vitro, in vivo and in silico, have played an increasingly indispensable role in understanding and controlling biological phenomena. Among them, it is of great interest to understand how associative learning is formed at the molecular circuit level. Noticeably, mathematical models have been increasingly used to predict the behaviors of molecular circuits. The Fernando’s model, which is thought to be one of the first works in this line of research using the Hill equation, attempted to design a synthetic circuit that mimics Hebbian learning in the neural network architecture. In this article, we carry out in-depth computational analysis of the model and demonstrate that the reinforcement effect can be achieved by choosing the proper parameter values. We also construct a novel circuit that can demonstrate forced dissociation, which was not observed in the Fernando’s model. Our work can be readily used as reference for synthetic biologists who consider implementing the circuits of this kind in biological systems.

More than 15,000 prescriptions and over the counter drugs are available according to the US Food and Drug Administration website. Moreover, several herbal medicines and dietary supplements are readily available to add to the list of possible drugs, which can potentially cause adverse drug interactions. These are a pressing concern for all as they can interfere with many dental procedures. Additionally, the number of geriatric patients seen in routine dental practice has increased over time. This implies that there are more patients with multiple diseases and health conditions like hypertension, diabetes, problems associated with the cardiovascular, renal and gastrointestinal systems, arthritis, osteoporosis, etc. All these require patients to be on certain medications. Furthermore, advancement in the dental field has led to more complex dental procedures (implants, grafts) being carried out in a general dental practice. These advanced and slightly more invasive treatments require the use of certain drugs before, during and after the treatment like local anesthetics, vasoconstrictors, anxiolytics, analgesics and antibiotics. All of these can possibly interact with medications a patient is already taking and can also interfere with the current dental treatment and create complications. This article aims to provide necessary information about commonly encountered systemic diseases and associated treating medications, their mechanism of action, possible complications and their management. The classes of drugs discussed include anti-platelet agents, vitamin K antagonists, novel oral anticoagulants, bisphosphonates, disease-modifying anti-rheumatic drugs and oral contraceptives.

(1) Background: This manuscript introduces the "Lines and Dots" (LAD) technique, a novel method for administering Botulinum Toxin Type A (BoNT-A) in treating horizontal forehead lines. This technique emphasizes precision in targeting nerve endplates, considering individual anatomical variations, and optimizing treatment efficacy. (2) Methods: The LAD technique focus on using the frontalis muscle contraction dynamics to identify the specific distribution of the supraorbital and supratrochlear nerves It involves creating a grid of predetermined lines and points on the forehead that align with nerve paths and motor endplate zones. (3) Results: By targeting injections along these precise lines and points, the LAD technique ensures more effective utilization of BoNT-A. This approach not only enhances the toxin's effect but also allows for a reduction in the overall dosage. The strategic placement of injections results in a more natural, symmetrical, and sustained therapeutic effect, ensuring an improved aesthetic outcome. (4) Conclusions: The LAD technique represents a significant advancement in the realm of cosmetic injectables. It offers a tailored, patient-specific approach, maximizing the effectiveness of BoNT-A injections for treating forehead lines while minimizing risks and enhancing patient satisfaction. This method underscores the importance of a deep anatomical understanding and precision in cosmetic procedures.

This study investigated the relationship between aluminum adjuvant vaccines and the prevalence of 4 childhood diseases (Autism, Allergies, Asthma, ADD/ADHD) using data from the 2020-2021 National Survey of Children's Health (NSCH) [1] and the Centers for Disease Control National Immunization Survey (CDC NIS) [2]. The study found an association with aluminum adjuvant dosage and the prevalence of each disease studied (Autism, Allergies, Asthma, ADD/ADHD) through a weighted regression analysis of disease prevalence against the summed likelihood of aluminum adjuvant vaccine uptake.

A surgical technique aimed at rerouting aqueous humor (AH) outflow from the anterior chamber to the suprachoroidal space (SCS) without performing surgical cyclodialysis was developed to decrease intraocular pressure (IOP) in glaucoma patients. The surgical outcomes of the technique were retrospectively analyzed in fifty-eight patients. At 6, 12, and 24 months, the mean IOP decreased from 27.8±8.3 to 14.95.0 mmHg, median 15.0 (25th percentile (p25 )13.0; 75th percentile (p75) 18.0), and 15.23.3 mmHg; hypotensive medication use reduced from median (p25; p75) 3 (2; 3) to 0 (0; 2), 0 (0; 2), and 0 (0; 1.5), and complete success was achieved in 62.8%, 51.2%, and 32.5% cases, with partial success in 28.4%, 44.2%, and 62.5% cases, respectively. Eight cases (13.8%) presented unsatisfactory outcomes. Intra- and postoperative complications were few and manageable. No bleb formation was observed in any of the cases. In 50% of cases, conjunctival lymphatic vessels (CLVs) developed following surgery in superior quadrants. The technique is safe and effective in providing a long-term decrease in IOP and hypotensive medication use. It was hypothesized in this study that the IOP decrease occurred as a result of enhanced AH outflow from the SCS to CLVs through intrascleral microchannels connecting the SCS to CLVs.

Oligonucleotide conjugates with boron clusters have found applications in different fields of molecular biology, biotechnology, and biomedicine as potential agents for boron neutron capture therapy, siRNA components, and antisense agents. Particularly, closo-dodecaborate anion represents a high-boron containing residue with remarkable chemical stability and low toxicity, suitable for the engineering of different constructs for biomedicine and molecular biology. In the present work, we synthesized novel oligonucleotide conjugates of closo-dodecaborate attached to the 5'-, 3'-, or both terminal positions of DNA, RNA, 2'-O-Me RNA, and 2'-F-Py RNA oligomers. For their synthesis, we employed click reaction with the azido derivative of closo-dodecaborate. The key physicochemical characteristics of the conjugates have been investigated using high-performance liquid chromatography, gel electrophoresis, UV thermal melting, and circular dichroism spectroscopy. Incorporation of closo-dodecaborate residues at the 3'-end of all oligomers stabilized their complementary complexes, while analogous 5'-modification decreased duplex stability. Two boron clusters attached to the opposite ends of the oligomer only slightly influence the stability of complementary complexes of RNA oligonucleotide and its 2'-O-methyl and 2'-fluoro analogs. On the contrary, the same modification of DNA oligonucleotides significantly destabilized DNA/DNA duplex but gave a strong stabilization of the duplex with RNA target. According to CD spectroscopy results, two terminal closo-dodecaborate residues cause a prominent structural rearrangement of complementary complexes with a substantial shift from B-form to the A-form of the double helix. The revealed changes of key characteristics of oligonucleotides caused by incorporation of terminal boron clusters, such as the increase of hydrophobicity, change of duplex stability, and prominent structural changes for DNA conjugates, should be taken into account for the development of antisense oligonucleotides, siRNAs, or aptamers bearing boron clusters. These features may also be used for engineering of developing NA constructs with pre-defined properties.

Detection of partial discharge (PD) activities in high-voltage equipment can be done according to the several mechanisms of signal detection, which are electromagnetic wave signal detection, acoustic signal detection, chemical reactions, electrical signal detection, or optical emission detection. Recently, multiple methods of detection and localization of partial discharge activities occurred in power transformers and gas-insulated switchgear (GIS) have been proposed to monitor the health condition of high-voltage equipment, especially when the awareness regarding preventive maintenance has been emphasized at the industrial level and electrical providers. In aligning the needs of industrial and the improvement of PD detection methods, this manuscript focused on reviewing the current practice methods for the detection and localization of PD signals in high-voltage equipment and comparing their efficacy, in summarizing the future direction of research work-related methods of PD detection. The comparative reviews are discussed in terms of the mechanism of PD signal detection, indication parameters, calibration technique, advantages, and limitations of each method of PD measurement in detail.

Tubulin superfamily (TSF) proteins are widespread and known for multifaceted roles as cytoskeletal proteins underpinning many basic cellular functions including morphogenesis, division, and motility. In eukaryotes, tubulin assembles into microtubules, a major component of the dynamic cytoskeletal network of fibres, whereas the bacterial homolog FtsZ assembles the division ring at midcell. Functions of the lesser-known archaeal TSF proteins are beginning to be identified, and show surprising diversity, including homologs of tubulin and FtsZ, and a third archaea-specific family, CetZ, implicated in the regulation of cell shape and possibly other unknown functions. In this study, we defined sequence and structural characteristics of the CetZ family and CetZ1 and CetZ2 subfamilies, identified CetZ groups and diversity amongst archaea, and identified potential functional relationships through analysis of the genomic neighbourhoods of cetZ genes. At least three subfamilies of orthologous CetZ proteins were identified in the archaeal class Halobacteria, including CetZ1 and CetZ2 and a novel uncharacterized subfamily. CetZ1 and CetZ2 were correlated to one another and to cell shape and motility phenotypes across diverse Halobacteria. Amongst other known CetZ clusters in orders Archaeoglobales, Methanomicrobiales, Methanosarcinales, and Thermococcales, an additional uncharacterized group from Archaeoglobales and Methanomicrobiales affiliated strongly with Halobacteria CetZs, suggesting they originated via horizontal transfer. Subgroups of Halobacteria CetZ2 and Thermococcales CetZ genes were found adjacent to different type IV pili regulons, suggesting a potential utilization of CetZs by type IV systems. More broadly conserved cetZ gene neighbourhoods included nucleotide and cofactor biosynthesis (e.g., F420) and predicted cell surface sugar epimerase genes. The findings imply that CetZ subfamilies are involved in multiple functions linked to the cell surface, biosynthesis and motility.

One of the most important objectives of the studies worldwide is to improve the performance of automotive engines to reduce fuel consumption and environmental pollution. Accordingly, the principal motivation of this research study is improving the tribological behavior of the piston ring/cylinder liner interfaces as a promising and straightforward approach in automotive fuel economy and increasing engine durability using Al₂O₃ and TiO₂ nanomaterials as smart nano-lubricant additives that adapted to different operating conditions by replenishing mechanisms anti-friction and anti-wear in automotive engines.

According to architectural standards, the common proportion of a rectangular-shaped classroom is the shallow proportion, which has a longer external room facade versus the perpendicular internal sides. Even in the Kingdom of Saudi Arabia (KSA), the same proportion is used in school projects. Environmentally, this proportion is logical when considering the role of adequate natural lighting for classroom visual functions, which could be more easily achieved if its longest side is the external one. But, the environmental efficiency of any architectural space cannot be only judged according to a single human comfort achievement, especially with the diverse environmental characteristics of places around the world. This diversity can show a defect in other human comfort achievements or other environmental issues in different ways when achieving a certain function in a unified way. A holistic study should be done for any common architectural shape or proportion to ensure their priority among other options in achieving maximum green architectural principles for a specific location before confirming and using it. The manuscript compares a rectangular classroom of different external/internal wall proportions to search for their preference to be used in Taif city schools in KSA. The compared case studies have different window variations and similarities to include their effect too. According to the overall green principles assessment, the results showed that the common proportion of classrooms didn’t give the higher green credits, which alerts us that the traditional rectangular classroom proportion is not always optimum for all regions including Taif city in KSA.

We are living in a world where people always strive for the luxuries they can get with less hard work and for these smart systems are developed and established all over the world to make life easier for the people. However, in Pakistan being a third-world country we are unable to achieve better results due to the lack of proper transit from one area to another. Sometimes the roads are not in their optimum conditions and hence people have to face a lot of problems while traveling. In urban areas, people cannot reach their destination in time, in some cases, they damage their vehicles due to the cracks on the roads, in medical emergency patient dies most of the time in their transit from rescuing point to the hospital. Similarly, in rural areas where farmers face countless problems while bringing their yield of the season towards the markets. Therefore, having described the severe damage the bad quality of roads is making. A solution is proposed to solve the problems of both the rural and urban population in our project. The project aims to provide the solution to their problem to a certain extent by monitoring the conditions of the roads. The sensors in the system will calculate the values and send them to the cloud server. The cloud server used is the blynk platform where the data will be stored. Moreover, data can be provided to the government in the future for the timely maintenance of the roads, and hence the citizens and lifestyle of the people will be changed. It is expected that the problems of both urban and rural population will be solved to a greater percentage.

Satellite-based broad-scale (i.e., global and continental) human settlement data offer foundational information for diverse applications spanning climate hazard mitigation, sustainable development monitoring, spatial epidemiology, and demographic modeling. While many human settlement products report exceptional detection accuracies above 85%, there is a substantial blind spot in that product validation is typically centered on large urban areas rather than rural, small-scale settlements that are home to 3.4 billion people. In this study, we make use of a data-rich collection of 30 refugee settlements in Uganda to produce a targeted assessment of small-scale settlement detection by four broad-scale human settlement products: Global Human Settlements Built-Up Sentinel-2 (GHS-BUILT-S2), World Settlement Footprint (WSF), High Resolution Settlement Layer (HRSL), and Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). We measured each product’s areal coverage within refugee settlements, assessed product detection accuracies in comparison to an independent dataset of 317,416 refugee settlement building footprints, and examined agreement between products. For refugee settlements established before 2016, the human settlement products had a low median F1-Score (F1) of 0.24, a high median false alarm rate of 0.59, and tended to only agree at locations of highest building density. Individually, WSF entirely overlooked 8 of the 30 study refugee settlements (median F1=0.17); GHS-BUILT-S2 underestimated the building footprint area by a median 50% (F1=0.15); GRID3 overestimated the building footprint area by a median 280% (F1=0.38); and HRSL underestimated the median area by 7% (F1=0.34). All products suffer from low detection accuracy and high false alarm rates, but GRID3 and HRSL, based on 0.5 meter resolution imagery, offer better detection accuracy than GHS-BUILT S2 and WSF, which are based on 10-30 meter resolution imagery. These results show that human settlement products have far to go in providing an accurate depiction of small-scale refugee settlements and would benefit from incorporating refugee settlements in training and validation of broad-scale human settlement detection.

Analysis of Fatigue Strain, Fatigue Modulus and Fatigue Damage for the modeling of concrete plays a vital role in the evolution material behaviour which is heterogeneous and anisotropic in nature. In this paper, the Level-S nonlinear fatigue strain curve, fatigue modulus curve, residual strain curve of concrete in compression, tension, flexure and torsional fatigue loading were proposed using strain life approach. The parameters such as physical meaning, the ranges, and the impact on the shape of the curve were discussed. Then, the evolution model of fatigue modulus was established based on the fatigue strain evolution model, fatigue modulus evaluation model, residual strain evaluation model, secondary strain evaluation model. The hypothesis of fatigue modulus is inversely related with the fatigue strain amplitude. The fatigue evolution of concrete damages the bond between material grains, changed the orientation of structure of molecules and affects the elastic properties resulting in the reduction of material stiffness and modulus by utilizing strain life analysis, regarding stiffness degradation and inelastic deformation by formation of microcracking, macro cracking, cracking which is heterogeneous and anisotropic in nature . This paper presents the Fatigue Strain Life Model and analyses of fatigue strain, fatigue modulus and damage parameters of concrete which is capable of predicting stiffness degradation, inelastic deformation, strength reduction under fatigue loading. Hence, the obtainable results were compared with experimental results for the validation of the proposed model.

The past years saw the rise of genomic biobanks and mega-scale meta-analysis of genomic data that promise to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limit the global understanding of disease risk and intervention efficacy, but also inhibit viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared, and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable, computable, operate without access to raw data due to privacy concerns. But they must be comparable, both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of commonly used genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks, locally and internationally, increase the accuracy of association analyses, and inform developmental efforts.

Objectives: To determine the effects of caffeine consumption on the sleep habits and lifestyle of medical students. Methods: A cross-sectional study was conducted at Jinnah Sindh Medical University (JSMU) and Hamdard College of Medicine. On 422 undergraduate students aged 18-25 years, through random sampling. The duration of the study was from January 2019 to June 2019. The data was collected through self-administered questionnaire which included data regarding sleep habits and lifestyle of medical students. Results: Majority (81.6%) of the students consumed caffeine while only (18.4%) did not. One third of the participants (31.8%) reported caffeine consumption increased their academic performance and (57.3%) reported that it does not. More than half of the participants (63.3%) who consumed caffeine slept during class, whereas (47.2%) never had difficulty in falling asleep during the night. Conclusion: This research concluded that caffeine does have some role on sleep habits of medical students as they tend to have less sleep hours, experience day time dysfunction, average quality of sleep, and falling asleep during class. It has been concluded that caffeine has no effect on eating habits of medical students however, it does increase the screening time, keeping them active.

NUMMI was one of the most analyzed case studies in terms of joint ventures, management dysfunction, and international globalization. NUMMI is an acronym for New United Motor Manufacturing, Inc. This manufacturer was a joint venture between automotive US titan GM and Toyota of Japan. GM wanted to further monetize its Fremont factory, but also had limited opportunities during a US economical recession. Toyota wanted to expand manufacturing operations in the US for the very first time, creating an intriguing collaborative partnership between the two. However, various problems lead to dysfunction through cultural, organizational, or managerial differences. This case study is analyzed through its historical analogical scope, ultimately leading to hypothesizing remediation through an ethical data-driven and total quality management (TQM) approach.

Few prior works study self-driving cars by deep learning with IoT collaboration. SDC-Net, which is an end-to-end multitask self-driving car camera cocoon IoT-based system, is one of the research that tackles this direction. However, by design SDC-Net is not able to identify the accident locations, it only classifies if it is a crash scene or not. In this work, we introduce an enhanced design for the SDC-Net system by 1) replacing the classification network with a detection one, 2) adapting our benchmark dataset labels built on the CARLA simulator to include the vehicles bounding boxes while keeping the same training, validation, and testing samples, 3) modifying the shared information via IoT to include the accident location. We keep the same path planning and automatic emergency braking network, the digital automation platform, and the input representations to formulate the comparative study. SDC-Net++ system is proposed to 1) output the relevant control actions, especially in case of accidents: accelerate, decelerate, maneuver, and brake, and 2) share the most critical information to the connected vehicles via IoT, especially the accident locations. A comparative study is also conducted between SDC-Net and SDC-Net++ with the same input representations: front camera only, panorama and bird-eye views, and with single-task networks: crash avoidance only, and multitask networks. Multitask network with a BEV input representation outperforms the nearest representation in precision, recall, f1-score, and accuracy by more than 15.134%, 12.046%, 13.593%, and 5%, respectively. SDC-Net++ multitask network with BEV outperforms SDC-Net multitask with BEV in precision, recall, f1-score, accuracy, and average MSE by more than 2.201%, 2.8%, 2.505%, 2%, and 18.677% respectively.

The incorporation of polycarboxylate ether superplasticizer (PCE) type polymer and silica fume (SF) in high-performance concretes (HPC) leads to the achievement of remarkable rheological and mechanical improvements. In the fresh state, PCEs are adsorbed on cement particles and dispersants, in turn promoting the workability of the concrete. Silica fume enables a very well compacted concrete to be obtained, which is characterized by high mechanical parameters in its hardened state. Some PCEs are incompatible with silica fume, which can result in the loss of slump and in poor rheological behavior. The main objective of the research is the study of the influence of three types of PCEs, which all have a different molecular architecture, on the rheological and mechanical behavior of high-performance concretes containing 10% of SF as a partial replacement of cement. The results show that the carboxylic density of PCE has an influence on its compatibility with SF.

Listwaenite rocks are widely spread in Fenja area of the Semail ophiolite of Oman and in Islam Abad area of the Neyriz ophiolite of Iran. There are three types of listwaenites found in these regions: silica-, carbonate-, and carbonate-silica (which includes dolomite, calcite, and magnesite. The alteration of host harzburgites started with hydrothermal alteration to serpentinite, followed by carbonation and silicification of serpentinite. Calcite- and magnesite-dolomite- listwaenites are more abundant in the Fenja area of Oman, while dolomite-listwaenites are more abundant in Islam Abad area in Iran. The mineralogy of listwaenites varies in both Iran and Oman; common minerals include quartz, calcite, goethite, magnesite, dolomite, serpentine, hematite, magnetite, Cr-mica, and Cr-spinel The major element chemistry of the different types of listwaenites in both Fenja and Islam Abad area generally comparable, and is largely similar to that of hydrothermally carbonated harzburgites, serpentinite, and listwaenites worldwide, despite spanning extraordinary and highly variable contents in major oxides, such as CaO, SiO2, MgO and LOI. Relict texture and common occurrence of Cr-spinel as well as the high concentrations of Cr, Ni and Co suggest that the protolith of the listwaenites in both regions was serpentinized harzburgites and serpentines. In comparison to the primary mantle and chondrite in spider diagrams, the Neyriz listwaenites have higher trace and REE element abundances than comparable listwaenites in the Fenja region. Harzburgite-normalized patterns of trace elements and REE in serpentinite and listwaenites overlap the average composition of harzburgite. PM-normalized trace element and REE patterns for serpentinized harzburgite and serpentinite show enrichment in Cs, U, Pb and Sr, with no Eu anomaly, comparable to mantle wedge serpentinites. The variable and high abundances of Ca, Mg, Ba, Zr, Sr, Pb, Zn, Mo and W in the carbonate- and silica-carbonate listwaenites, with unique Si enrichment and Mg, Na2O, Zr, Y, Ba, Sr, Rb, Cu, Pb, Sc, Cs, Nb, Mo and W. depletion in silica listwaenites are indicative of large fluctuations in major and trace element mobility. Cr, Ni and Co were immobile during alteration Enrichment in Ca and Si could occur by internal or late outside supply. Ca, Mg and Si are conceivably the foremost mobile major components amid harzburgite and serpentinite carbonation with mobilization confirmed by formation of quartz and Mg-carbonate in silica-carbonate listwaenites and quartz in silica listwaenites. The listwaenites in Islam Abad and Fenja area were formed due to hydrothermal alteration of serpentinite along thrust faults and shear zones which acted as pathway for Ca and/or Si rich fluids. The intensity of deformation in Islamabad listwaenites has been higher than Fenja listwaenites as indicated by higher abundance of trace elements.

High seismic activity in the Himalayas and the increasing urbanization of its surrounding areas in the northern Indian region pose significant threats to both lives and properties. To mitigate the risk of seismic events, an earthquake early warning system can be used in the region. This system would be particularly beneficial to cities and towns in the mountainous and foothill regions that are located near earthquake sources. The government and the science and engineering community have re-sponded to this call by establishing the Uttarakhand State Earthquake Early Warning System (UEEWS). The system became fully operational on August 4, 2021, after being launched by the government of Uttarakhand. The UEEWS includes 170 accelerometers in the seismogenic part of the Uttarakhand region of the Himalayas. Ground motion data is transmitted to a central server through a dedicated private telecommunication network 24 hours a day, seven days a week.The system is designed to issue warnings for moderate to high-magnitude earthquakes via a mobile application installed on users' devices and sirens installed in government-owned public buildings. The UEEWS has successfully issued alerts for light earthquakes that occurred in the instrumented region and warnings for moderate earthquakes that occurred in the vicinity of the instrumented area. This paper provides an overview of the design of the UEEWS, details of the instrumentation, adaptation of attributes and their relation to earthquake parameters, the operational flow of the system, and information about the dissemination of warnings

Understanding swash zone dynamics is of crucial importance for coastal management as the swash motion, consisting of the uprush of the wave on the beach face and the subsequent downrush, is responsible for driving changes the beach morphology trough sediment exchanges between the sub-aerial and sub-aqueous beach. Improved understanding of the probabilistic characteristics of these motions has the potential to allow coastal engineers to develop improved sediment transport models which, in turn, can be further developed into coastal management tools. In this paper, novel descriptors of swash motions are obtained by combining field data and statistical modelling. Our results indicate that the probability distribution function (PDF) of shoreline height (p(ζ)) and trough-to-peak swash heights (p(ρ)) measured at a high energy, sandy beach were both inherently multimodal. Based on the observed multimodality of these PDFs, Gaussian Mixtures are shown to be the best method to statistically model them. Further, our results show that both offshore and surf zone dynamics are responsible for driving swash zone dynamics, which indicates unsaturated swash. The novel methods and results developed in this paper, both data collection and analysis, could aid coastal managers to develop improved swash zone models in the future.

Chronological age represents the greatest risk factor for many life-threatening diseases including neurodegeneration, cancer and cardiovascular disease; ageing also increases susceptibility to infectious disease. Current therapies that effectively tackle individual diseases may have little impact on the overall healthspan of older individuals, who would still be vulnerable to other age-related pathologies. However, recent progress in ageing research has highlighted the accumulation of senescent cells with chronological age as a probable underlying cause of pathological ageing. Cellular senescence is an essentially irreversible proliferation arrest mechanism that has important roles in development, wound healing and preventing cancer, but it may limit tissue function and cause widespread inflammation with age. The serine/threonine kinase mTOR is a regulatory nexus heavily implicated in both ageing and senescence. Excitingly, a growing body of research has highlighted rapamycin and other mTOR inhibitors as promising treatments for a broad spectrum of age-related pathologies, including neurodegeneration, cancer, immunosenescence, osteoporosis, rheumatoid arthritis, age-related blindness, diabetic nephropathy, muscular dystrophy, and cardiovascular disease. In this review, we assess the use of mTOR inhibitors to treat age-related pathologies, discuss possible molecular mechanisms of action where evidence is available, and consider strategies to minimize undesirable side effects. We also emphasize the urgent need for reliable, non-invasive biomarkers of senescence and biological ageing to better monitor the efficacy of any healthy ageing therapy.

Plasma being the fourth and most abundant form of matter extensively exists in the universe in the inter-galactic regions. It provides an electrically neutral medium of unbound negative and positive charged particles, which has been produced by subjecting air and various other gaseous mixtures to strengthen the electromagnetic field and by heating compressed air or inert gasses for creating negative and positive charged particles known as ions. Nowadays, many researchers are paying attention to the formation of artificial Plasma and its potential benefits for mankind. The literature is sparsely populated with the applications of Plasma. This paper presents specific methods of generation and applications of Plasma, which benefits humankind in various fields, such as in electrical, mechanical, chemical and medical fields. These applications include hydrogen production from alcohol, copper bonding, semiconductor processing, surface treatment, Plasma polymerization, coating, Plasma display panels, antenna beam forming, nanotechnology, Plasma Torch, Plasma pencils, low-current non-thermal Plasmatron, treatment of prostate cancer, Plasma source ion implantation, cutting by Plasma, Plasma etching, pollution control, neutralization of liquid radioactive waste, etc. Resultantly, worth of Plasma technology in the medical industry is increasing exponentially that is closing the gap between its benefits and cost of equipment used for generating and controlling it.

Omics technologies, viz., genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal breeding program because they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in cereal-omics promise—in combination with time efficiency—the cost benefits. In this review, we provide a comprehensive overview of the established cereal-omics methods in five major cereals, viz., rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants, (2) high-density transcriptomics data to study gene expression patterns, (3) global and targeted proteome profiling to study protein structure and interaction, (4) metabolomic profiling to quantify organ level small-density metabolites and their composition, and (5) high-resolution high-throughput image-based phenomics approaches are surveyed in this review.

Background: The role played by the non-dominant parietal lobe in motor cognition, attention and spatial awareness networks has potentiated the use of awake surgery. When this is not feasible, asleep monitoring and mapping techniques should be used to achieve an onco-functional balance. Objective: This study aims to assess the feasibility of a dual-strip method to obtain direct cortical stimulation for continuous real-time cortical monitoring and subcortical mapping of motor and visual pathways simultaneously in parietal lobe tumour surgery. Methods: Single-centre prospective study between May’19-November’20 of patients with intrinsic non-dominant parietal-lobe tumours. Two subdural strips were used to simultaneously map and monitor motor and visual pathways. Results: Fifteen patients were included. With regards to motor function, a large proportion of patients had abnormal interhemispheric resting motor threshold ratio (iRMTr) (71.4%), abnormal Cortical Excitability Score (CES) (85.7%), close distance to the corticospinal tract – Lesion-To-Tract Distance (LTD) – 4.2mm, Cavity-To-Tract Distance (CTD) – 7mm and intraoperative subcortical distance - 6.4mm. Concerning visual function, the LTD and CTD for optic radiations (OR) were 0.5mm and 3.4mm, respectively; the mean intensity for positive subcortical stimulation of OR was 12mA±2.3mA and 5/6 patients with deterioration of VEPs>50% had persistent hemianopia and transgression of ORs. 12 patients remained stable, one patient had a de-novo transitory hemiparesis, and two showed improvements in motor symptoms. A higher iRMTr for lower limbs was related with a worse motor outcome (p=0.013) and a longer CTD to OR was directly related with a better visual outcome (p=0.041). At 2 weeks after hospital discharge, all patients were ambulatory at home and all proceeded to have oncological treatment. Conclusion: We propose motor and visual function boundaries for asleep surgery of intrinsic non-dominant parietal tumours. Pre-operative abnormal cortical excitability of the motor cortex, deterioration of the VEP recordings and CTD<2mm from the OR were related to poorer outcomes.

Citation frequencies represent the most significant contributions in any respective field. This bibliometric analysis aimed to identify and analyze the 100 most-cited publications in the field of antibiotics and to highlight the trends of research in this field. “All databases” of Clarivate Analytics' Web of Science was used to identify and analyze the 100 publications. The articles were then cross-matched with Scopus and Google Scholar. The frequency of citation ranged from 940 to 11051 for the Web of Science, 1053 to 10740 for Scopus, and 1162 to 20041 for Google Scholar. Five hundred thirteen authors made contributions to the ranked list, and Robert E.W. Hancock contributed in six articles, which made it to the ranked list. Sixty-six scientific contributions originated from the United States of America. In contrast, five publications were linked to the University of Manitoba, Canada, that was identified as the educational organization, which made the most contributions (n=5). According to the methodological design, 26 of the most cited works were review-type closely followed by 23 expert opinions/perspectives. Eight articles were published in Nature journal, making it the journal with the most scientific contribution in this field. Correlation analysis between the publication age and citation frequency was found statistically significant (P = .012).

Retinoic acid receptor-related orphan receptor γ (RORγ) is a transcription factor regulating the expression of the pro-inflammatory cytokine IL-17 in human T helper 17 (Th17) cells. Activating RORγ can induce multiple IL-17-mediated autoimmune diseases but may also be useful for anticancer therapy. Its deep immunological functions make RORɣ an attractive drug target. Over 100 crystal structures have been published describing atomic interactions between RORɣ and agonists and inverse agonists. In this review, we focus on the role of dynamic properties and plasticity of the RORɣ orthosteric and allosteric binding sites by examining structural information from crystal structures and simulated models. We discuss the possible influences of allosteric ligands on the orthosteric binding site. We find that high structural plasticity favors the druggability of RORɣ, especially for allosteric ligands.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.

Rebar cages form the skeletal framework of reinforced concrete structural members. They comprise longitudinal and transverse reinforcing bars, usually connected by tie wires. Past studies have identified tie-wire connections as the "weak links" in large, prefabricated rebar cages, leading to their failure during site handling and construction stages. Recent research has explored the use of mechanical U-bolt connectors to bolster stability and safety of rebar cages while reducing their vulnerability and risk of failure. This paper presents a comprehensive experimental and numerical investigation of a new type of mechanical connector, referred to as "Cage Clamp", to enhance rebar cage stability and safety. Component-level experimental tests are conducted to determine the force-displacement response of Cage Clamp connectors for crossbar connections in different degrees of freedom. The results highlight the remarkable strength and stiffness of Cage Clamp connectors, significantly outperforming traditional tie-wire connections. Furthermore, full-scale experimental tests are performed on a circular underground pile-shaft rebar cage with Cage Clamp connectors to assess its behavior under various site handling conditions. The data obtained from these experiments are used to construct and refine detailed 3D finite element models of the rebar cages, capable of capturing the complex behavior of rebar cages with Cage Clamp connectors. Using the numerical model, a sensitivity analysis is performed to assess the effect of the number of Cage Clamps on the deflection and stability of the rebar cage. The findings show that using cage clamps to connect pick-up rebar with lateral reinforcement at every 8 to 10 feet is sufficient to ensure the stability of the cage during typical site handling conditions. The results of this study serve as a basis for establishing analysis, design, fabrication, and handling guidelines for rebar cages, contributing to safe and efficient construction practices.

Research rarely explores LGBTQ+ youth bullying in the context of culture-specific outcomes (e.g., LGBTQ+ identity development) and what can mitigate the impact of peer stressors. This study used a concurrent mixed methods design to explore how experiences of peer victimization predicted LGBTQ+ youth’s identity development (i.e., stigma sensitivity, concealment motivation, and difficult process) and whether social support and outness served as protective, moderating factors. The mixed-methods approach provides a culture-specific context via qualitative inquiry to inform whether the quantitative findings align with how youth qualitatively discuss their experience of bullying, negative outcomes, and social support. Our sample consisted of 349 LGBTQ+ youth 14-17 years old who completed a survey (quantitative sample), and a subset of 39 LGBTQ+ youth who completed a semi-structured interview (qualitative sample). Our quantitative findings indicated that greater overall peer victimization was positively related to LGBIS-revised subscales of stigma sensitivity, concealment motivation, and difficult process, where both outness and social support moderated such relations. Qualitatively, victimized youth also reported stigma sensitivity and concealment motivation, while also endorsing how being out and having a support system played a role in their experience of being victimized. These qualitative findings align with our quantitative findings that classmate support mitigated the effects of peer victimization on difficulty of coming out. Implications for practitioners and researchers are provided.

In this study, we introduce the dynamics of a Hepatitis B virus (HBV) model with the class of asymptomatic carriers and conduct a comprehensive analysis to explore its theoretical aspects and examine the crossover effect within the HBV model. To investigate the crossover behavior of the operators, we divide the study interval into two subintervals. In the first interval, the classical derivative is employed to study the qualitative properties of the proposed system, while in the second interval, we utilize the ABC fractional differential operator. Consequently, the study is initiated using the piecewise Atangana-Baleanu derivative framework for the systems. The HBV model is then analyzed to determine the existence, Hyers-Ulam (HU) stability, and disease-free equilibrium point of the model. Moreover, we showcase the application of an Adams-type predictor-corrector (PC) technique for Atangana-Baleanu derivatives and an extended Adams-Bashforth-Moulton (ABM) method for Caputo derivatives through numerical results. Subsequently, we employ computational methods to numerically solve the models and visually present the obtained outcomes using different fractional-order values. This network is designed to provide more precise information for disease modeling, considering that communities often interact with one another, and the rate of disease spread is influenced by this factor.

Biofilms are complex communities of microorganisms that adhere to surfaces and develop a protective matrix. The colonization of devices in the food and health care industries by microbial biofilms poses numerous risks. Existing antimicrobial agents often fail to penetrate the biofilm matrix, allowing the pathogen to grow and persist. The objective of this study was to evaluate the impact of MADIO PRO+ multipurpose disinfectant on Salmonella Typhimurium biofilm using crystal violet assay and FTIR spectroscopy. Results demonstrated that MADIO PRO+ multipurpose disinfectant significantly (p<0.05) inhibited biomass of S. Typhimurium biofilm and altered the structure of S. Typhimurium biofilm. In conclusion, MADIO PRO+ multipurpose disinfectant offers an advantage in biofilm control strategy. This discovery could help the food and health care industries to plan better microbial intervention strategies.

MPC (Magneto-Photonic Crystal) Optimisation is a feature-rich Windows software application designed to enable researchers to analyze the optical and magneto-optical spectral properties of multilayers containing gyrotropic constituents. A set of computational algorithms aimed at enabling the design optimization and optical or magneto-optical (MO) spectral analysis of 1D magnetic photonic crystals (MPC) is reported, together with its Windows software implementation. Relevant material property datasets (e.g., the optical spectra of refractive index, absorption, and gyration) of several important optical and MO materials are included, enabling easy reproduction of the previously published results from the field of MPC-based Faraday rotator development, and an effective demonstration-quality introduction of future users to the multiple features of this package. We also report on the methods and algorithms used to obtain the absorption coefficient spectral dispersion datasets for new materials, for which the film thickness, transmission spectrum, and refractive index dispersion function are known.

Skin cancer is an exquisite disease globally nowadays. Because of the poor contrast and apparent resemblance between skin and lesions, automatic identification of skin cancer is complicated. The rate of human death can be massively reduced if melanoma skin cancer can be detected quickly using dermoscopy images. In this research, an anisotropic diffusion filtering method is used on dermoscopy images to remove multiplicative speckle noise and the fast-bounding box (FBB) method is applied to segment the skin cancer region. Furthermore, the paper consists of two feature extractor parts. One of the two features extractor parts is the hybrid feature extractor (HFE) part and another is the convolutional neural network VGG19 based CNN feature extractor part. The HFE portion combines three feature extraction approaches into a single fused feature vector: Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), and Speed Up Robust Feature (SURF). The CNN method also is used to extract additional features from test and training datasets. This two-feature vector is fused to design the classification model. This classifier performs the classification of dermoscopy images whether it is melanoma or non-melanoma skin cancer. The proposed methodology is performed on two ordinary datasets and achieved the accuracy 99.85%, sensitivity 91.65%, and specificity 95.70%, which makes it more successful than previous machine learning algorithms.

Type 1 diabetes (T1D) is an autoimmune condition where the body’s immune cells destroy their insulin-producing pancreatic beta-cells leading to dysregulated glycaemia. Individuals with T1D control their blood glucose through exogenous insulin replacement therapy, often using multiple daily injections or pumps. However, failure to accurately mimic intrinsic glucose regulation results in glucose fluctuations and long-term complications impacting key organs such as the heart, kidneys, and/or the eyes. It is well-established that genetic and environmental factors contribute to the initiation and progression of type 1 diabetes, but recent studies show that epigenetic modifications are also important. Here, we discuss key epigenetic modifications associated with type 1 diabetes pathogenesis and discuss how recent research is finding ways to harness epigenetic mechanisms to prevent, reverse, or manage type 1 diabetes.

Immunosensors have been widely developed to use antibodies to detect a pathogen of interest; it is interesting to look at the effect of nonspecific antibody binding to E. coli using electrochemical methods. IgG antibody not specific to E. coli O157:H7 was crosslinked onto a screen-printed carbon electrode. The presence of E. coli at 4, 4 × 10², 4 × 10⁵, and 4 × 10⁸ CFU/mL on the electrode surface was detected via linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). Current transfer at both electrodes was reduced as the concentration of bacteria increased; however, the calibration of number of cells to decreased current was nonlinear for IgG-modified electrodes. The nonlinearity is confirmed by EIS measurements which showed highest impedance at 4 CFU/mL E. coli when impedance should be the lowest. FESEM images showed higher binding of cells when IgG is present compared to electrodes with reduced graphene oxide (rGO) alone. Electrodes with rGO alone show less attachment of E. coli, with EIS showing a linear calibration profile, while LSV shows not much difference in current values for all concentrations aside from the highest concentration. These results suggest that nonspecific binding can provide false signals in electrochemical measurements, and it is crucial to provide proper controls.

The effect of hybrid carbon fillers of multi-walled carbon nanotubes (CNT) and carbon black (CB) on the electrical and morphological properties of polystyrene (PS) nanocomposites were systematically investigated in microinjection molding (μIM). The polymer nanocomposites with three different filler concentrations (i.e. 3, 5 and 10 wt%) at various weight ratios of CNT/CB (100/0, 30/70, 50/50, 70/30, 0/100) were prepared by melt blending, then followed by μIM under a defined set of processing conditions. A rectangular mold insert which has three consecutive zones with decreasing thickness along the flow direction was adopted to study abrupt changes in mold geometry on the properties of resultant microparts. The distribution of carbon fillers within microparts was observed by scanning electron microscope, which was correlated with electrical conductivity measurements. Results indicated that there is a flow-induced orientation of incorporated carbon fillers and this orientation increased with increasing shearing effect along the flow direction. High structure CB is found to be more effective than CNT in terms of enhancing the electrical conductivity, which was attributed to the good dispersion of CB in PS and their ability to form conductive networks via self-assembly. Morphology observations indicated that there is a shear-induced depletion of CB particles in the shear layer, which is due to the marked difference of shear rates between the shear and core layers of the molded microparts. Moreover, an annealing treatment is beneficial to enhance the electrical conductivity of CNT-containing microparts.

This study empirically investigates the complex interplay between the severity of the coronavirus pandemic, mobility changes in retail and recreation, transit stations, workplaces, and residential areas, and lockdown measures in 88 countries of the word. To conduct the study, data on mobility patterns, socioeconomic and demographic characteristics of people, lockdown measures, and coronavirus pandemic were collected from multiple sources (e.g., Google, UNDP, UN, BBC, Oxford University, Worldometer). A Structural Equation Modeling (SEM) technique is used to investigate the direct and indirect effects of independent variables on dependent variables considering the intervening effects of mediators. Results show that lockdown measures have significant effects to encourage people to maintain social distancing. However, pandemic severity and socioeconomic and institutional factors have limited effects to sustain social distancing practice. The results also explain that socioeconomic and institutional factors of urbanity and modernity have significant effects on pandemic severity. Countries with a higher number of elderly people, employment in the service sector, and higher globalization trend are the worst victims of the coronavirus pandemic (e.g., USA, UK, Italy, and Spain). Social distancing measures are reasonably effective at tempering the severity of the pandemic.

Abstract: Insecure and portable devices in the smart city’s Internet of Things (IoT) network are increasing at an incredible rate. Various distributed and centralized platforms against cyber-attacks have been implemented in recent years, but these platforms are inefficient due to their constrained levels of storage, high energy consumption, the central point of failure, underutilized resources, high latency, and etc. In addition, the current architecture confronts the problems of scalability, flexibility, complexity, monitoring, managing & collecting of IoT data, and defend against cyber-threats. To address these issues, the author presents distributed and decentralized Blockchain-Software Defined Networking (SDN) based energy-optimized architecture for IoT in smart cities. Thus, SDN continuous observing, controlling, managing IoT devices activities and detect possible attacks in the network; Blockchain provides adequate security & privacy against cyber-attacks, reduces the central point of failure issues; Network Function Virtualization (NFV) are used to saving energy, load balancing, as well as increasing the lifetime of the entire network. Also, we introduce a Cluster Head Selection (CHS) algorithm to reduce the energy consumption in the presented model. Finally, we analyze the performance using various parameters (e.g. throughput, response time, gas consumption, communication overhead) and demonstrating the result that provides higher throughput, lower response time, lower gas consumption than existing works for smart cities.

The current report contributes to the understanding of the stereoselectivity of the chiral dirhodium(II) carboxylate catalysts derived from N-protected amino acid ligands. Investigating the possible effect of ligand stereo-purity on catalyst structure and enantioselectivity was carried out. This was justified through a new X-ray crystal structure for Rh2(S,S,S,R-PTTL)4 diastereomer.

A study of photovoltaic solar window technologies is reported, focusing on their structural features, functional materials, system development, and suitability for use in practical field applications, e.g. public infrastructures and agricultural installations. Energy generation performance characteristics are summarized and compared to theory-limit predictions. Working examples of pilot-trial solar window-based installations are described. We also report on achieving electric power outputs of about 25 W_p/m² from clear and transparent large-area glass-based solar windows.

Single-molecule magnets (SMMs) have garnered significant interest in the field of molecular magnetism due to their unique magnetic properties at the nanoscale. These molecular systems exhibit magnetisation behaviour reminiscent of conventional bulk magnets but with distinct advantages such as size-dependent properties and potential applications in quantum computing and high-density data storage. However, challenges remain in harnessing their properties for practical applications, including their susceptibility to degradation and limited control over their assembly and organisation.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system adjustments and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs. generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO₂ emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and the Rest of PJM region leading to scenario-varying changes in the plant-level release of several air pollutants. Due to air pollution chemistry and transport and socio-demographics, these changes in turn give rise to a reduction of 10 to 182 PM_2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Scenarios that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, vulnerable populations—in both PA and Rest of PJM—benefit most in scenarios that prioritize plant closures in PA near Environmental Justice Areas. These results demonstrate the importance of considering cross-regional linkages and socio-demographics in designing equitable retirement strategies.

We present a review of the current state of the field for a rapidly evolving group of technologies related to solar energy harvesting in built environments. In particular, we focus on recent achievements in enabling the widespread distributed generation of electric energy assisted by energy capture in semi-transparent or even optically clear glazing systems and building wall areas. Whilst concentrating on the cutting-edge recent results achieved in the integration of traditional photovoltaic device types into novel concentrator-type windows and glazings, we compare the main performance characteristics reported with these achievable using more conventional (opaque or semi-transparent) solar cell technologies. A critical overview of the current status and future application potential of multiple existing and emergent energy harvesting technologies for building integration is provided.

The emergence of CDK4/6 inhibitors, such as palbociclib, ribociclib, and abemaciclib, has revolutionized the treatment landscape for hormone receptor-positive breast cancer. These agents have demonstrated significant clinical benefits in terms of both progression-free survival and overall survival. However, resistance to CDK4/6 inhibitors remains a challenge, limiting their long-term efficacy. Understanding the complex mechanisms driving resistance is crucial for the development of novel therapeutic strategies and improvement of patient outcomes. Translational research efforts, such as preclinical models and biomarker studies, offer valuable insight into resistance mechanisms and may guide the identification of novel combination therapies. This review paper aims to outline the reported mechanisms underlying CDK4/6 inhibitor resistance, drawing insights from both clinical data and translational research in order to help direct the future of treatment for hormone receptor positive metastatic breast cancer.

Due to its built-up chemoresistance after prolonged usage, the demand for replacing platinum in metal-based drugs (MBD) is rising. The first MBD approved by the FDA for cancer therapy was cisplatin in 1978. Even after nearly four and a half decades of trials, there has been no significant improvement in osteosarcoma (OS) therapy. In fact, many MBD have been developed, but the chemoresistance problem raised by platinum remains unresolved. This motivates us to elucidate the possibilities of the copper and zinc (CuZn) combination to replace platinum in MBD. Thus, the anti-chemoresistance properties of CuZn and their physiological functions for OS therapy are highlighted. Herein, we summarise their chelators, main organic solvents, and ligand functions in their structures that are involved in anti-chemoresistance properties. Through this review, it is rational to discuss their ligands’ roles as biosensors in drug delivery systems. Hereafter, an in-depth understanding of their redox and photoactive function relationships is provided. The disadvantage is that the other functions of biosensors cannot be elaborated on here. As a result, this review is being developed, which is expected to intensify OS drugs with higher cure rates. Nonetheless, this advancement intends to solve the major chemoresistance obstacle towards clinical efficacy.

Amorphous ferrite-type rare-earth (RE) substituted garnets and garnet-oxide nanocomposite layers are prepared on clear glass substrates by using RF magnetron sputter-deposition process. By using a combination approach employing custom-built spectrum-fitting software in conjunction with Swanepoel’s envelope method, the spectral dispersion function of optical constants and the layer thicknesses are derived accurately from the transmission spectra of the as-deposited samples. The effects of excess metal-oxides added to the base material systems during the co-deposition process are found to affect the refractive index and the optical absorption coefficients of garnet-oxide composites. A number of optical constant datasets are presented, enabling the experimentalists to design nanophotonic or integrated-optics devices employing these functional materials.

Glacial ripping is a newly recognized process sequence in which subglacial erosion is triggered by groundwater overpressure. Investigations in gneiss terrain in lowland Sweden indicate that ripping involves three stages of (i) hydraulic jacking, (ii) rock disruption under subglacial traction and (iii) glacial transport of rock blocks. Evidence for each stage includes, respectively, dilated fractures with sediment fills, disintegrated roches moutonnées and boulder spreads. Here we ask: can glacial ripping also occur in sedimentary rocks, and, if so, what are its effects? The case study area is in hard, thinly bedded, gently dipping Cambrian quartz-arenites at Loch Eriboll, NW Scotland. Field surveys reveal dilated, sediment filled, bedding-parallel fractures, open joints and brecciated zones, interpreted as markers for pervasive, shallow penetration of the quartz-arenite by water at over-pressure. Other features, including disintegrated rock surfaces, boulder spreads and monomict rubble tills, indicate glacial disruption and short distance subglacial transport. The field results, together with published cosmogenic isotope ages, indicate that glacial ripping operated with high impact close to the former ice margin at Loch Eriboll at 17.6-16.5 ka. Glacial ripping thus can operate effectively in bedded, hard sedimentary rocks and the accompanying brecciation is significant – if not dominant - in till formation. Candidate markers for glacial ripping are identified in other sedimentary terrains in former glaciated areas of the Northern Hemisphere.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged &gt;19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and &gt;12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

There is a need for strategic healthcare workforce planning to address shortages and ensure universal health coverage, aiming to optimize work-force per population ratio, distribution, and competencies. Amidst rising demands exacerbated by aging populations and events like the COVID-19 pandemic, strategic workforce planning becomes crucial for addressing healthcare inequalities by forecasting needs, bridging skill gaps, and adapting to changing demographics and care models. Israel has invested in strategic planning to tackle healthcare workforce challenges; however, globally there is insufficient planning informed by health labor market analysis, which hinders efforts to address healthcare inequalities. The paper reviews national policies in Israel, Australia, Germany, and Norway, ex-amining statistics and government publications to highlight strategic plan-ning considerations and address challenges in healthcare workforce plan-ning. This paper focuses both on the critical role of physicians in healthcare systems, and on the changing borders between healthcare professions and different national contexts which demand more context dependent strategic workforce planning. We highlight common themes among national policies, including the need for data collection, increasing the capacity of domestic training programs, and the need to address geographic maldistribution of physicians. Ultimately, we aim to guide policy in the development of a re-silient and sustainable healthcare workforce capable of meeting diverse community needs and promoting equity in healthcare services.

The circadian clock is a 24-hour cycle within the body that regulates various factors, including sleep, body temperature, and hormone secretion. It allows the body to adjust to the light and dark cycle. Disruptions to the circadian rhythm are important risk factors for many diseases, including neurodegenerative illnesses. The central clock is controlled by the clock genes in the suprachiasmatic nucleus (SCN) of the brain, and one of the main functions of the circadian clock is to regulate lipid metabolism. There has been a lack of investigation on the circadian regulation of lipid metabolism-related apolipoprotein genes in the brain; thus, this study sought to summarize the rhythmic expression of clock genes and lipid metabolism-related apolipoprotein genes within the SCN of Mus musculus. Out of the 20 apolipoprotein genes that were studied by the published database, all 9 genes were highly expressed in the SCN. Most of the 6 genes showed rhythmic expression in the brain of mice, suggesting that the master clock might regulate them. The results, therefore, reveal a potential target for preventing and treating circadian disorders. We summarized most studies of lipid-related apolipoprotein genes within limited locations of the SCN and brain to further understand how disordered cerebral lipid metabolism causes multiple brain diseases and disorders. We reviewed recent studies, determined the unexplored questions, and identified a potential direction for further research.

Inflammatory Bowel Disease (IBD) is characterized by chronic remitting and relapsing inflammation of the lower gastrointestinal tract. The etiology underlying IBD remains unknown but is thought to involve a hypersensitive immune response to environmental antigen, including the microbiota. Diagnosis and monitoring of disease is heavily reliant on endoscopy, which is invasive and does not provide information regarding specific mediators. This review describes recent developments in imaging of IBD with a focus on PET and SPECT imaging of inflammatory mediators, and how this may be applied to the microbiota.

Antiphospholipid antibody syndrome (APS) is an autoimmune disorder characterised by thrombosis and the presence of antiphospholipid antibodies (aPL): lupus anticoagulant and/or IgG/IgM anti-β2-glycoprotein I and anticardiolipin antibodies. APS carries significant morbidity for a relatively young patient population from recurrent thrombosis in any vascular bed (arterial, venous or microvascular), often despite current standard of care, which is anticoagulation with vitamin K antagonists (VKA). Platelets have established roles in thrombosis at any site, and platelet hyperreactivity is clearly demonstrated in the pathophysiology of APS. Together with excess thrombin generation, platelet activation and aggregation are the common end result of all the pathophysiological pathways leading to thrombosis in APS. However, antiplatelet therapies play little role in APS, reserved as a possible option of low dose aspirin in addition to VKA in arterial or refractory thrombosis. This review outlines the current evidence and mechanisms for excessive platelet activation in APS, how it plays a central role in APS-related thrombosis, what evidence for antiplatelets is available in clinical outcomes studies and potential future avenues to define how to target platelet hyperreactivity better with minimal impact on haemostasis.

The proximal part of the colon offers opportunities to prolong the absorption window following oral administration of a drug. In this work, we used computer simulations to understand how the hydrodynamics in the proximal colon might affect the release from dosage forms designed to target the colon. For this purpose, we developed and compared three different models: a completely-filled colon, a partially-filled colon and a partially-filled colon with a gaseous phase present (gas-liquid model).The highest velocities of the liquid were found in the completely-filled model, which also shows the best mixing profile, defined by the distribution of tracking particles over time. No significant differences with regard to the mixing and velocity profiles were found between the partially-filled model and the gas-liquid model. The fastest transit time of an undissolved tablet was found in the completely-filled model. The velocities of the liquid in the gas-liquid model are slightly higher along the colon than in the partially-filled model. The filling level has an impact on the exsisting shear forces and shear rates, which are decisive factors in the development of new drugs and formulations.

The study titled "Molecular Choreography of DNA: Insights and Innovations" explores the intricate dance of DNA, shedding light on its structure, function, and regulation. This comprehensive review delves into the historical significance of DNA research, from Watson and Crick's double helix discovery to recent innovations in genomics and molecular biology. The review highlights DNA's roles in replication, repair, gene regulation, and chromatin dynamics, emphasizing the precision and complexity of its molecular choreography. Innovations like CRISPR-Cas9 gene editing and advanced sequencing technologies have revolutionized our understanding of DNA, opening new avenues for scientific exploration. This study aims to provide readers with a deeper appreciation of DNA's central role in life's choreographed processes.

Causal language can be a powerful tool for media outlets to subtly influence public perception and reinforce specific narratives. Therefore, identifying these linguistic patterns can be helpful in assessing the level of bias present in media content. In this paper, we directly compare the prevalence of causal language in headlines pertaining to the coverage of the Israel-Palestine conflict and the Russia-Ukraine war. We specifically look at the BBC and AlJazeera headlines covering the assault on Gaza since October 7, 2023. We use UniCausal, a model for causal text mining, in order to automatically extract the cause and effect of each headline. Our findings reveal that BBC headlines tend to avoid directly attributing causality to Israel for the violence in Gaza, whereas Al Jazeera headlines explicitly identify Israel as the responsible party. This differential use of causal language suggests a potential bias in media reporting.

This work explores the use of Kuhn verdazyl radicals as building blocks in multifunctional molecular materials in an exemplary study, focusing on the magnetic and the electron transfer (ET) characteristics, but also addressing the question whether chemical modification by cross-coupling is possible. The ET in solution is studied spectroscopically whereas solid state measurements afford information about the magnetic susceptibility or the conductivity of the given samples. The observed results are rationalized based on the chemical structures of the molecules, which have been obtained by X-ray crystallography. The crystallographically observed molecular structures as well as the interpretation based on the spectroscopic and physical measurements are backed up by DFT calculations. The measurements indicate that only weak, antiferromagnetic coupling is observed in Kuhn verdazyls owed to the low tendency to form face-to-face stacks, but also that steric reasons alone are not sufficient to explain this behavior. Furthermore, it is also demonstrated that ET reactions proceed rapidly in verdazyls/verdazylium redox couples and that Kuhn verdazyls are suited as donor molecules in ET reactions.

In this article, bio-composites derived from starch-glycerol biodegradable matrix reinforced with jute fibers have been fabricated using the wet hand lay-up and compression moulding techniques. Samples having different weight percentages of jute fiber in the starch matrix have been analysed. The fibers surface was chemically treated by alkaline sodium hydroxide for improving the interphase bonding between fiber and matrix. Tensile test for the composites were done and the sample with highest tensile strength was selected for further tests that included water absorption, scanning electron microscopy and thermal analysis. It has been concluded that the ultimate tensile strength was found to be maximum for the composition of 15% fiber by weight composite as 7.547 MPa without epoxy coating and 10.43 MPa with epoxy coating. The major disadvantage of bio-composite is its high water absorption property, which in this study has been inhibited by the epoxy resin layer. Herein, the results of various tests done disclose a noteworthy improvement in the overall properties of bio-composite, in comparison to the neat biodegradable starch matrix.

Most of the literature on the optimization problem of transportation in supply chain networks (SCN) considered fixed costs (FC). However, in the practical applications of this problem it is important to study the effect of FC. This paper examines the impact of fixed cost increase as well as the variable cost on the optimization of a Two-Stage SCN. To do so, two mathematical models for mixed-integer nonlinear programming are developed. The first model optimizes fixed and variable costs in addition to the opening cost, whereas the second model only optimizes variable and opening costs. To evaluate the effect of considering FC on the optimization supply chain problem, four groups of instances are randomly generated, and solved using Lingo. The results of the two models are compared utilizing the average percentage deviation. In addition, sensitivity analysis is performed to determine the impact of changes in opening and variable costs on the considered optimization problem. The computational results and the sensitivity analysis show that the first model with minimized FC outperforms the second model, which does not consider the FC in minimization and FC affect the optimization.

There has been no significant efficacy in treatment for osteosarcoma (OS) metastasis after nearly four decades of trials. This motivates us to elucidate OS therapies according to their four bidirectional mutation stages. To refresh the OS therapy status quo, the historical developments and clinical advancements are briefly described. However, the main issue of metastasis remains unresolved, accounting for 90% of pulmonary metastasis deaths. Thus, this metastasis problem is related to immune evasion and chemoresistance that are being induced after long-term treatment by the use of immunotherapy for tumorigenesis. Therefore, it is rationale to discuss the relationship cycles of mutation stages including tumorigenesis, metastasis, immune evasion, and chemoresistance. Even though many combinational and targeted therapies have been developed to intensify these mutation treatments, successful clinical translations with higher cure rates are still rare. Through this review, an in-depth understanding of the bidirectional relationship between the four OS mutation stages and their respective therapies is provided. Herein, we summarise the medicines used to treat tumorigenesis, including COLGALT2 inhibitors, Tra2B, and AGAP1, miR-148a and miR-21-5p EVs, and the lncRNA LIFR-AS1. Following the medicines used to treat metastasis are AXL, miR-135a-5p, mRNA BCL6, TGFβ1, Tim-3, SOCS5, CASC15, KLF3-AS1, PDCD4, ATG5, and Rab22a-NeoF1. Then the medicines used to treat immune evasion are N-cadherin, anti-IL-9, USP12 inhibitor, IgG-4+ B-cells, LAP inhibitor, anti-Wnt2 mAb, anti-αvβ8 integrin, HK2-mediated IκBα, IDO inhibitor with NO, and TGF-βRII with anti-IgG1. Finally, the medicines used to treat chemoresistance are DHFR, FPGS, HSP-90AA1, XCT-790, ATKI, and IGF1. As a result, this contribution is expected to serve as a reference and guide for scientists and clinicians.

This article will briefly review the progress of h-BN based solid-state metal semiconductor metal (MSM) neutron detectors. In the last decade, several groups have been working on hexagonal boron nitride (h-BN) based solid-state neutron detectors. Recently, the detection efficiency of 59% has been reported. Efficient, low-cost neutron detectors made from readily available materials are essential for various applications. Neutron detectors are widely used to detect fissile materials and nuclear power plants for security applications. The most common and widely used neutron detectors are 3He based, which are sometimes bulky, difficult to transport, have high absorption length, need relatively high bias voltage (>1000 V), and have low Q-value (0.764 MeV). Also, 3He is not readily available material. Thus, there is a strong need to find an alternative detection material. 10B isotope has a high neutron absorption cross-section, and it has been tested as a coating on the semiconducting materials. Due to the two-step process, neutron capture through 10B, and then electron-hole pair generation in a typical semiconducting material, the efficiency of these devices is not up to the mark. The progress in h-BN based detectors requires a review to envision the further improvement in this technology.

In the past decade, considerable efforts have been devoted to the development of semitransparent organic solar cells. Numerous materials and architectures have been proposed for the future commercialization of these devices. Among these, the use of ternary active layers demonstrated a great promise for the development of efficient semi-transparent organic solar cells with the potential for future applications including self-powered greenhouses and powered windows. Researchers seek alternative solutions to the trade-off between device power conversion efficiency (PCE) and average visible transmittance (AVT), with photoactive materials being the key parameters that govern both (PCE) and (AVT) as well as device stability. Several new organic materials, including polymers and small molecules, were synthesized, and used in conjunction with a variety of techniques to achieve semitransparent conditions. In this review paper, we will look at the working principle and key parameters of semi-transparent organic solar cells, as well as the methods that have been used to improve the performance of ternary-based semi-transparent organic solar cells. The main approaches were concluded to be spectral enhancement and transparency increment of the active layer through bandgap tuning, utilizing novel organic semiconductors, and design architecture of the active layers.

The Combined Elevation Test (CET) is a musculoskeletal screening technique (MST) replicates the streamline position in swimming and is commonly used in various sports. Although the CET is widely used, no normative data exist within an adolescent population. Therefore, the purpose of this study was to develop a normative data set for the CET within an adolescent population and to evaluate the influence various demographic and anthropometric variables. Data was collected for 416 participants aged between 8 and 18 years old. Age and arm span showed a significant correlation with CET scores (arm span r_s (105) = .478, p = .000, age r_s (416) = .238 p = .000). Regression analysis further quantified the influence of arm span and age on CET scores accounting for 23.1% and 5.3% of variability respectively. These results can be used as a reference point for clinicians and coaches who are using the CET within their assessment.

This paper evaluates the global sustainable competitiveness of three blocks of power (US, China and EU) based on OGT (Organic Growth Theory) structure. In addition, a sensitivity analysis of COVID-19 on three measures of global sustainable competitiveness, economy, environment and social is also presented. OGT is a well-thought-through and standard framework for evaluation of any type of organiza-tion in their pathway to experience truly sustainable growth. GDP (Gross Domestic Product) is used as an economic measure; total carbon emissions equivalent is used as an environmental measure and HMI (Human Development Index) as a social measure. It is concluded that the pandemic has paused the evolution of countries to be truly world centric countries. However, the recovery plans seem to be highly aligned with the OGT scores and it is expected that the scores to improve dramatically.

Innovation and technology are important tools of minerals sector efficiency and productivity im-provement. The uptake of technologies has proven important levelrs to improve the productivity of mining sector. This paper provides a comprehensive analysis of mine-level productivity by using a global data of copper, gold, and platinum from 1991-2020. Various drivers of proioductivity have been analysed to draw policy insights. Empirical findings reveal significant disparities in technical efficiency and productivity across mines and regions. A further decomposition of TFP into its different components suggest that the adoption of innovative practices and investment in technology adoption could improve the overall productivity of these commodities. The findings also suggest that an appropriate input mix and optimal scale of production could boost platinum mining productivity. Regional disparities in productivity in different commodities (e.g., South Africa vs. Zimbabwe) give policymakers with insights into how to support production scale and productivity through appropriate input mixtures.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.

The COVID-19 pandemic is due to infection caused by the novel SARS-CoV-2 that impacts the lower respiratory tract. The spectrum of symptoms ranges from asymptomatic infections to mild respiratory symptoms to the lethal form of COVID-19 which is associated with severe pneumonia, acute respiratory distress and fatality. At present, the global case fatality rate of COVID-19 laboratory confirmed cases is ~4.7% ranging from ~0.3-0.4% in Chile and Israel to ~10.8% in Italy. To address this global crisis, up-to-date information on the viral genomics and transcriptomics is crucial for understanding the origins and global dispersal of the virus, providing insight into viral pathogenicity, transmission and epidemiology, and enabling strategies for therapeutic interventions, drug discovery and vaccine development. Therefore, this review provides a comprehensive overview of COVID-19 epidemiology, genomic etiology, findings from recent transcriptomic map analysis, viral-human protein interactions, molecular diagnostics, and the current status of vaccine and novel therapeutic intervention development. Moreover, we provide an extensive list of resources that will help the scientific community access numerous types of databases related to SARS-CoV-2 OMICs and approaches to therapeutics related to COVID-19 treatment.

Herewith we report a facile synthesis of zinc oxide doped with (5, 10, 15, and 20 wt%) titanium oxide nanocomposites in gelatin under ultra-sonication. The X-ray diffraction (XRD) data revealed ZnO the formation in addition to a rutile phase TiO2. The ZnO phase size decreased, and the rutile TiO2 phase increased with a TiO2 loading increment. The scanning electron microscopy (SEM) displayed a combination of spherical and hexagonal particles with a 60 – 80 nm size distribution. The prepared nanostructures photocatalytic activity was assisted using Rhodamine B dye, where they showed enhanced photodegradation competence under visible light irradiation. The kinetics of photodegradation followed the first-order kinetics with the 20 % wt sample having the maximum activity. The mechanistic investigation revealed the dominance of h+ and •O2- species during the dye photodegradation. The results indicate the potential application of such gelatin stabilized nanostructures for dye illumination from aqueous solutions under sunlight.

The present work encompasses an application-oriented perspective to the possible employment of gold nanoparticles as nanomedicine in cancer therapeutics. The rationale of the work lies in the growing needs for assessment of advanced alternative treatment of cancer employing functionalized nanoparticles as nanomedicine. Gold nanoparticles fabricated via green chemistry methods by leaves of a time-honored medicinal plant, Piper betle were ascertained for their synthesis and properties under the umbrella of characterization of nanoparticles, through various techniques like UV-vis spectroscopy, FTIR spectroscopy, X-ray diffraction, and scanning electron microscopy. The cytotoxicity assay of well-characterized gold nanoparticles was monitored against lung cancer cell line (A549) by metabolic and imaging assays. MTT assay or the metabolic assay was performed for a range of nanoparticles’ concentrations. The results were promising and proved to be a leading-edge venture, envisaging the possibility of gold nanoparticles for cancer therapeutics.

Machine Learning (ML) has brought about a transformative era in reactor operations, reshaping monitoring, control, and optimization strategies. This survey comprehensively explores the diverse spectrum of ML applications in industrial reactors. From real-time sensor analysis ensuring reactor functionality to adaptive control algorithms ensuring stability, ML's impact is profound and multifaceted. The benefits of ML are equally evident in optimization, encompassing performance trend prediction, proactive maintenance, and fine-tuning of operations for enhanced efficiency. This review identifies dominant ML techniques, operations stages receptive to ML integration, core data sources, and critical input-output parameters. Aimed at both academics and practitioners, this exploration enriches reactor technologies, unlocking their full potential through insights driven by ML.

The outbreak of coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions and has affected more than 100 countries in recent weeks. It is imperative that global healthcare systems are prepared. Containment initiatives in Jordan, on the other hand, have decreased new cases by over 63%. The Jordanian national health system has been very pleased with its ability to adequately meet the needs of the patients diagnosed with SARS-CoV-2 pneumonia, and includes intensive care. From 2 March to 14 April 2020, between 4% and 8% of active infected patients in Jordan registered daily in intensive care. The percentage is very low.

Purpose The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals has created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of an image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology, etc. Design/methodology/approach The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training Deep Learning (DL) models on thousands of images of these tests using transfer learning, this paper i) classifies the type of the assay, and ii) classifies the colourimetric results. Findings This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time. Originality/value To the best of our knowledge, this is the first attempt to provide Colourimetric Assay Type Classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.

Malaysian healthcare institutions still use ineffective paper-based vaccination systems to manage childhood immunization schedules. This may lead to missed appointments, incomplete vaccinations, and outbreaks of preventable diseases among infants. To address this issue, we proposed a text messaging vaccination reminder and recall system named Virtual Health Connect (VHC) to simplify and accelerate the immunization administration for nurses that may result in improving the completion and timeliness of immunizations among infants. Considering the narrow research about the acceptance of these systems in the healthcare sector, we examined factors influencing nurses’ attitude and intention to use VHC using the extended technology acceptance model (TAM). The novelty of the conceptual model is proposing new predictors of attitude, namely, perceived compatibility and perceived privacy and security issues. We conducted a survey among 121 nurses in Malaysian government hospitals and clinics to test the model. We analyzed the collected data using partial least squares-structural equation modeling (PLS-SEM) to examine the significant factors influencing nurses’ attitude and intention to use VHC. Moreover, we applied artificial neural network (ANN) to determine the most significant factors of acceptance with higher accuracy. Therefore, we could offer more accurate insights to decision-makers in the healthcare sector for the advancement of health services. Our results highlighted that the compatibility of VHC with the current work setting of nurses developed their positive perspectives toward the system. Moreover, the nurses felt optimistic about the system when considering it to be useful and easy to use in the workplace. Finally, their attitude toward using VHC played a pivotal role in raising their intention. Based on the ANN models, we also found that perceived compatibility was the most significant factor influencing nurses' attitude towards using VHC, followed by perceived ease of use and perceived usefulness.

Cloudburst is one of the most devastating and frequently occurring natural hazardous events in Indian Himalayan region. Localized deep cumulus convective clouds have a capability of giving enormous amount of rainfall over a limited horizontal area, within a short span of time. Whenever, such events occur, lead to flash floods causing landslides, house collapses, dislocation of traffic, and human casualties on a large scale. Therefore, it is necessary to predict the cloudburst inundation zones accurately to avoid damage associated with them. For this, high resolution Digital Elevation Model generated from CartoSat-1 (Stereo pair) were integrated in MIKE 11 Hydrodynamic 1D model to generate longitudinal profile of the study area and to find water level, peak discharge, flow velocity, flow width at different reaches along the Asi ganga and Bhagirathi river, to know the Cloudburst flood inundation scenario. On 3^rd August 2012 one of the major Cloudburst event occurred in Asi Ganga Valley in Indian Himalayan region which was considered for simulation of hydrodynamic model. For a Cloudburst event, 100 mm/hr rainfall was considered for the simulation of the hydrodynamic model. It is observed that the discharge rise from 50 m³/s to 549.164 m³/s (an abrupt increase of about 10 times) within 1 hr at Sangamchetty in Asiganga river and at Joshiyara area rise from 600 m³/s to 3378.69 m³/s (an abrupt increase of about 5 times) within 4 hr in Bhagirathi river. Similarly the water level rises around 3 m and 6m in Asi Ganga and Bhagirathi rivers respectively. Flash Flood inundation areas due to Cloudburst on 3^rd August 2012 were demarcated from the simulation results in GIS environment.

We obtain exact solutions to the field equations for 5 dimensional LRS Bianchi type-I spacetime in $f(R,T)$ theory of gravity where specifically the following three cases are considered: (i) $f(R,T)=\mu(R+T)$, (ii) $f(R,T)=R \mu + R T \mu^2$ and (iii) $f(R,T)=R+\mu R^2+\mu T$ where $R$ and $T$ respectively the Ricci scalar and trace of the energy-momentum tensor. It is found that the equation of state (EOS) parameter $w$ is governed by the parameter $\mu$ involved in the $f(R,T)$ expressions. We fine-tune the parameter $\mu$ to obtain effect of phantom energy in the model, however we also restrict this parameter to obtain a stable model of the universe. It is noted that the model isotropizes at finite cosmic time.

Nanofibres have gained increasing attention due to their advantages of having a high porous structure, narrow pore size and distribution, and a high specific surface area. One of the most efficient techniques for producing nanofibres is via electrospinning. Nanofibres are currently being used in various fields, including water filtration. Although nanofibres possess the ability to filter various components, the fibres generally have a low mechanical strength that can mitigate the performance over time. Therefore, in overcoming this issue, several studies have focused on improving the strength of the nanofibre membranes for a water filtration application. This review discusses the advantages and challenges of nanofibres for water filtration membranes and summarises the methods to increase the strength of the membranes, including solvent vapour, thermal treatment, and chemical crosslinking.

Polyethylene terephthalate (PET) pollution poses significant environmental consequences, and thus new degradation methods must be explored to mitigate this problem. We previously demonstrated that a consortium of three Pseudomonas and two Bacillus species can synergistically degrade PET in culture. The consortium more readily consumes Bis(2-Hydroxyethyl) terephthalate (BHET), a byproduct made in PET depolymerization, compared to PET, and can fully convert BHET into metabolically usable monomers terephthalic acid (TPA) and ethylene glycol (EG). Because of its crystalline structure, the main limitation of the biodegradation of post-consumer PET is the initial transesterification from PET to BHET, depicting the need for the transesterification step in the degradation process. Additionally, there have been numerous studies done on the depolymerization reaction of PET to BHET, yet few have tested the biocompatibility of that product with a bacterial consortium. In this report, a two-step process was implemented for sustainable PET biodegradation, where PET is first depolymerized to form BHET using an Orange Peel Ash (OPA) catalyzed glycolysis reaction, followed by complete degradation of the BHET glycolysis product by the bacterial consortium. Results show that OPA-catalyzed glycolysis reactions can fully depolymerize PET, with an average BHET yield of 92% (w/w) and that the reaction product is biocompatible with the bacterial consortium. After inoculation with the consortium, 19% degradation of the glycolysis product was observed in 2 weeks, for a total degradation percentage of 17% when taking both steps into account. Furthermore, the 10-week total BHET degradation rate was 35%, demonstrating that the glycolysis products are biocompatible with the consortium for longer periods of time, for a total two-step degradation rate of 33% over 10 weeks. While we predict complete degradation is achievable using this method, further experimentation with the consortium can allow for a circular recycling process, where TPA can be recovered from culture media and reused to create new materials.

Background: The use of technology in paediatrics is increasing, and new health technology will change the way in which paediatric care is delivered in the future. This review is part of the Royal College of Paediatrics and Child Health Paediatrics 2040 project, which is developing a credible vision for the future of paediatrics in the UK. Aims: To summarise the impact of health technology on the delivery of paediatric care over the last ten years. To learn from existing technology use and make recommendations for future implementation. Methods: A search strategy was developed and two databases (Cochrane Library and PubMed) were systematically searched in August 2019 for relevant publications in English. Searches were limited to papers published between January 2009 and August 2019 (with further rapid review of papers published between September 2019 and November 2020). We included papers that studied young people up to the age of 24 or on those providing care for this population. A thematic synthesis of the data from the included studies was undertaken using seven domains of paediatric care. Results: 128 studies were included, grouped by domain of care. Most included studies were defined as digital (n=55) or communication (n=37). Studies looked at the different types of health technology used within different domains of care, including secondary and tertiary care (n=39), public health and prevention (n=29), and community (n=20). Studies were assessed on delivery of care outcomes using positive, negative, mixed and no effect. The most common outcomes reported were adherence and satisfaction. Discussion: This review highlights the growing importance of technology in delivering paediatric care. Six themes emerged: the importance of clear guidelines, continuity of care, confidentiality and privacy, digital poverty, using a personalised approach, and using technology to supplement rather than replace. In future, technology development should involve the end user throughout the design process.

Knowledge of the spatio-temporal occurrence of avalanche activity is critical for avalanche forecasting and hazard mapping. We present a near-real time automatic avalanche monitoring system that outputs detected avalanche polygons within roughly 10 min after Sentinel- 1 SAR data download. Our avalanche detection algorithm has an average probability of detection of 67.2 % with a false alarm rate averaging 45.9, with maximum POD's over 85 % and minimum FAR's of 24.9 % compared to manual detection of avalanches. The high variability in performance stems from the dynamic nature of snow in the Sentinel-1 data. After tuning parameters of the detection algorithm, we processed five years of Sentinel-1 images acquired over a 150 x 100 km large area in Northern Norway, with the best setup. Compared to a dataset of field-observed avalanches, 77.3 % were manually detectable. Using these manual detections as benchmark, the avalanche detection algorithm achieved an accuracy of 79 % with high POD's in cases of medium to large wet snow avalanches. For the first time, we can present a dataset of spatiotemporal avalanche activity over several winters from a large region. This unique dataset allows for research into the relationship between avalanche activity and triggering meteorological factors, mapping of avalanche prone areas and near-real time avalanche activity monitoring to assist public avalanche forecasting. Currently, the Norwegian Avalanche Warning Service is using our processing system for pre-operational use in three regions in Norway.

Poor soil health is a critical problem in many urban landscapes. Degraded soil restricts plant growth and microorganism activity, limiting the ability of urban landscapes to perform much needed ecosystem services. Incorporation of approximately 33% compost by volume into degraded soil has been proven to improve soil health and structure over time while avoiding the financial and environmental costs of importing soil mixes from elsewhere. However, additions of high volumes of compost could potentially increase the risk of nutrient loss through leaching and runoff. The objective of our study was to consider the effects of different compost amendments on soil health, plant health and susceptibility to nutrient leaching in order to identify ranges of acceptable compost characteristics that could be used for soil remediation in the urban landscape. We conducted a bioassay with Phaseolus vulgaris (Bush Bean) to measure the effect of nine composts from different feedstocks on various plant health parameters. We collected leachate prior to planting to measure nutrient loss from each treatment. We found that all compost amendments improved soil health. Nutrient-rich, manure-based composts produced the greatest plant growth, but also leached high concentrations of nitrate and phosphorus. Some treatments provided sufficient nutrients for plant growth without excess nutrient loss. We concluded, when incorporating as much as 33% compost by volume into a landscape bed, the optimal compost will generally have a C:N ratio of 10-20, P-content <1.0% and a soluble salt content between 1.0 and 3.5 mmhos/cm. These recommendations should ensure optimal plant and soil health and minimize nutrient leaching.

In recent years, the field of radiotherapy has witnessed remarkable advancements with the integration of artificial intelligence (AI) technologies into clinical practice. Traditionally, radiotherapy treatment planning has been a labor-intensive process, requiring meticulous manual segmentation and optimization. With the advent of AI, particularly deep learning algorithms, the accuracy and efficiency of target delineation and organ-at-risk segmentation have significantly improved. AI-driven algorithms analyze voluminous medical imaging data, enabling rapid and precise contouring, thus expediting the planning phase and reducing inter-observer variability. Furthermore, AI's role extends to treatment plan optimization, where it intelligently explores vast parameter spaces to generate optimal plans tailored to individual patients. This not only saves dosimetrists' time but also enhances plan quality by accounting for complex anatomical variations and personalized clinical goals. In the realm of treatment delivery, AI-powered real-time image guidance enhances the accuracy of patient positioning, ensuring precise radiation targeting. Adaptive radiotherapy, enabled by AI, allows on-the-fly plan modifications in response to anatomical changes, significantly improving treatment accuracy in scenarios like tumor shrinkage or weight loss. Beyond planning and delivery, AI algorithms contribute to outcome prediction by analyzing historical patient data and treatment responses. This predictive capability aids clinicians in making informed decisions and refining treatment strategies for better prognoses. Despite the revolutionary potential, challenges remain in seamlessly integrating AI into clinical workflows. Ethical considerations, data privacy, and algorithm interpretability necessitate cautious implementation. Additionally, fostering interdisciplinary collaboration between AI experts and radiation oncologists is imperative to harness the technology's full potential. This paper explores the impact of AI in four key areas of radiotherapy: automated segmentation, dosimetric and machine quality assurance, adaptive radiation therapy, and clinical outcome prediction.

The epigenetic mechanism of DNA methylation is essential for regulating gene expression and adaptation in plants, especially when exposed to various environmental stressors such as drought, heat, and nutrient availability. The impact of these stressors can lead to alterations in DNA methylation patterns and gene expression, which this study aims to investigate. Specifically, we are interested in understanding how DNA methylation plays a role in controlling the expression of stress-response genes, as well as genes involved in plant growth and development. To accomplish this, we are analyzing the changes in DNA methylation patterns and gene expression in response to different stressors like drought and heat. Our research findings suggest that DNA methylation is a vital regulator of plant adaptation to environmental stress, and we hope to gain further insight into these mechanisms by identifying genes that exhibit differential expression in response to stress and analyzing their DNA methylation status. This study offers valuable insights into the development of crops that can thrive under changing climate conditions.

We report on the development of several different thin-film functional material systems prepared by RF magnetron sputtering at Edith Cowan University nanofabrication labs. We conduct research on the design, prototyping, and practical fabrication of high-performance magneto-optic (MO) materials, oxide based sensor components, and heat regulation coatings for advanced construction and solar windows.

Biofilter application for treatment of stormwater containing de-icing chemicals commonly applied in airports, propylene glycol and potassium formate, was investigated. Lab-scale adsorption tests using filter media made of crushed clay (Filtralite) and granular activated carbon showed that adsorption was unsuitable for removal of propylene glycol and potassium formate. Column filtration experiment testing two different crushed clay size ranges was conducted. The results showed that DOC removal was dependent on a number of factors. This study investigated the impact of filter depth, nutrients addition, and filtration rate. DOC removal suggested that DOC degradation occurred on the top filter layer. It was shown that the most active separation occurred in the first ~20 cm of filter depth. This was confirmed by results from water quality analysis (i.e. DOC removal and ATP measurement) and calculations based on a filtration performance analysis (Iwasaki model) and filter hydraulic evaluation (Lindquist diagram). It was shown that for the highest C:N:P ratio tested (molar ratio of 24:7:1), 50-60% DOC removal was achieved. Addition of nutrients was found important and determining the biofilter performance.

Current research in the field of antimicrobials is focused on the development of novel antibiotics and antimicrobial agents to counteract the huge dilemma that the human population is mainly facing in regards to the rise of bacterial resistance and biofilm infections. Host Defense peptides (HDPs) are a promising group of molecules for antimicrobial development as they share unique characteristics suitable for antimicrobial activity including their broad spectrum of activity and potency against bacteria. AamAP1 is a novel HDP that was identified through molecular cloning from the venom of the North African scorpion Androctonus amoeruxi. In vitro antimicrobial assays revealed that the peptide displays moderate activity against different strains of Gram-positive and Gram-negative bacteria. Additionally, the peptide proved to be highly hemolytic and displaying significantly high toxicity against mammalian cells. In our study, a novel synthetic peptide analogue named A3 was designed from the naturally occurring scorpion venom host defense peptide. The design strategy depended on modifying the amino acid sequence of the parent peptide in order to increase its net positive charge, percentage helicity and optimize other physico-chemical parameters involved theoretically in HDPs activity. Accordingly, A3 was evaluated for its in vitro antimicrobial and anti-biofilm activity individually and in combination with four different types of conventional antibiotics against clinical isolates of multi-drug resistant (MDR) Gram-positive bacteria. A3 was also evaluated for its cytotoxicity against mammalian cells. A3 displayed potent and selective in vitro antimicrobial activities against a wide range of MDR Gram-positive bacteria. Our results also showed that combining A3 with conventional antibiotics displayed a synergistic mode of action which resulted in decreasing the MIC value for A3 peptide as low as 0.125 µM. These effective concentrations were associated with negligible toxicities on mammalian cells. In conclusion, A3 exhibits enhanced activity and selectivity when compared with the parent natural scorpion venom peptide. The combination of A3 with conventional antibiotics may be pursued as a potential novel treatment strategy against MDR and biofilm forming bacteria.

With the dramatic increase in world population, continued advances in modern greenhouse agriculture and plant growth practices are expected to help overcome the global problem of future food shortages. Next generation greenhouse design practices will need to address a range of issues, ranging from energy and land use efficiency to providing plant-optimised growth techniques. In this paper, we focus on investigating the optimum irradiation spectra matched to the lettuce species (Lactuca sativa, L.), which is commonly grown in greenhouse environments, in order to develop low-emissivity glass panes that maximize the biomass productivity of glass greenhouses. This low-emissivity glass passes the solar spectral components needed for crop growth, while rejecting other unwanted radiations, leading to significant energy savings and other beneficial effects related to greenhouse climate control, in a range of climates. This is due to reducing both the solar heat gain and photosaturation, which can raise the temperature of the crops to harmful levels. Experimental results show that substantial biomass productivity improvements in lettuce (up to ~14.7%) can be attained using spectrally optimized illumination, compared with white light irradiation. We also report on the development of advanced metal-dielectric thin-film filters that produce the optimum illumination spectrum when exposed to sunlight.

Since 2007, at the Electron Science Research Institute (ESRI) nano-fabrication laboratories, Edith Cowan University, Australia, we have devoted research efforts to the synthesis and characterization of bismuth-containing ferrite-garnet-type thin-film magneto-optic (MO) materials of different compositions. We report on the development and properties of highly bismuth-substituted iron-garnet thin films prepared by using radio frequency (RF) magnetron sputtering. We study the process parameters associated with the RF magnetron sputter deposition technique and investigate the results of optimizing process parameters and implementing several special techniques including the fabrication of co-sputtered nanocomposite films, all-garnet multilayer structures, applying oxygen plasma treatment on amorphous garnet layers just after the deposition process, and designing modifications of the annealing crystallization process and regimes for achieving the best MO properties. We demonstrated significant improvement in MO properties of Bi-containing ferrite-type garnet thin-film materials, including record-high MO figures of merit and improved conventional and un-conventional hysteresis loops of Faraday rotation. The attractive optical, magnetic, and magneto-optic properties obtained in highly bismuth-substituted iron garnet thin-film materials of multiple composition types are relevant in the context of manufacturing next-generation ultra-fast optoelectronic devices, such as light intensity switches and modulators, high-speed flat panel displays, and high-sensitivity sensors.

We report on the field testing datasets and performance evaluation results obtained from a commercial property-based visually-clear solar window installation site in Perth-Australia. This installation was fitted into a refurbished shopping centre entrance porch, and showcases the potential of glass curtain wall-based solar energy harvesting in built environments. In particular, we focus on photovoltaic (PV) performance characteristics such as the electric power output, specific yield, day-to-day consistency of peak output power, and the amounts of energy generated and stored daily. The dependencies of the generated electric power and stored energy on multiple environmental and geometric parameters are also studied. An overview of the current and future application potential of high-transparency, visually-clear solar window-based curtain wall installations suitable for practical building integration is provided.

This paper investigates an innovative photovoltaic cell configuration, denoted as “Au/CuSCN/RbGeI3/CdTe/ZnO/TiO2/FTO", using SCAPS-1D simulation. The research focuses on optimizing device performance by analyzing key components, including ZnO as the electron transport layer (ETL), RbGeI3 as the perovskite absorber layer, CuSCN as the hole transport layer (HTL), and CdTe as the active buffer layer. A comparison is made with the standard “Au/CuSCN/CH3NH3SnI3/CdTe/ZnO/TiO2/FTO" configuration under dark and illuminated conditions. Through an in-depth investigation involving temperature effects, generation rate analysis, RbGeI3 absorber layer thickness, Nd level, and interface defect levels, an optimized design for a unit area is achieved. The proposed solar cell demonstrates outstanding performance metrics, including an open circuit voltage (Voc) of 0.94V, a short circuit current density (Jsc) of 34.52mA/cm2, a fill factor (FF) of 77.77%, and an energy conversion efficiency (η) of 25.40%. These values significantly outperform the reference models with energy conversion efficiencies of 10.11% and 21.09%. Real-world applicability is validated by implementing these optimized characteristics in a photovoltaic system for Pakistan’s geographical location using PVSyst software. The suggested solar cell achieves a remarkable performance ratio (PR) of 85.6%, surpassing the PR of the reference basic solar cell model at 83%. The findings of this research offer a promising and superior solar cell design, incorporating innovative materials and optimization techniques to achieve exceptional energy conversion efficiency and overall performance. This study’s outcomes have the potential to advance photovoltaic technology and contribute to sustainable energy solutions worldwide.

Bioactive lipids are involved in cellular signalling events with links to human disease. Many of these are involved in inflammation under normal and pathological conditions. Despite being attractive molecules from a pharmacological point of view, detection and quantification of lipids has been a major challenge. Here, we have optimised a liquid chromatography dynamic multiple reaction monitoring targeted mass spectrometry (LC-dMRM-MS) approach to profile eicosanoids and fatty acids in biological samples. In particular, by applying this analytic workflow to study a cellular model of Chronic Myeloid Leukaemia (CML), we found that intra- and extra-cellular 2-Arachidonoylglycerol (2-AG), intracellular Arachidonic Acid (AA), and extracellular Prostaglandin F_2α (PGF_2α), 5-Hydroxyeicosatetraenoic acid (5-HETE), Palmitic acid (PA, C16:0) and Stearic acid (SA, C18:0) were altered in response to immunomodulation by type I Interferon (IFN-I), a currently approved treatment for CML. Our observations indicate changes in eicosanoid and fatty acid metabolism with potential relevance in the context of cancer inflammation and CML.

The popularity of multiparticulate formulations (MPs) as a paediatric dosage form continues to increase. MPs comprise of multiple small units that are easy-to-swallow. Currently, MPs are commonly manufactured into unit doses that are either swallowed whole or opened prior to administration. While this is an acceptable approach, dosing is envisioned to be optimized with a ‘standard’ paediatric device which can better harness the flexible dosing potential of MPs. We evaluated a novel oral syringe (SympfinyTM) that is being developed as a tool to dispense and administer MPs to children. Forty children, 4-12 years old, received 0.5, 1.2, and 2.0 mL doses of placebo MPs using the oral syringe with spring water or a drink of choice to complete sample intake. Acceptability was recorded as those able to completely swallow the dose and participants also rated dose acceptability on a 5-point scale. The ability to completely swallow the dose decreased as dose volume increased; the smallest dose was completely swallowed by 87.5% (35/40) children, and 69.4% (27/39) of children confirmed their willingness to take the sample as a daily medicine. Larger doses, 1.2 and 2.0 mL, gave values of 55% and 57.5% for the doses completely swallowed and 58.8% and 51.72% for willingness to take the sample as a daily medicine, respectively. Use of a drink of choice showed no increase in swallowability as compared with water. The novel oral syringe being developed is an appropriate device for dispensing doses flexibly and administering neutral tasting MPs directly to the mouth in the lower dose range without the need for a co-administration vehicle in children aged 4-12 years.

Food allergy has been recognised by the World Health Organisation as a chronic disease that could lead to fatality. The symptoms can mediate from mild to severe consequences. Some cases have reported that food allergy sufferers are bullied and are discriminated at workplace, thus increasing their stress level, apart from facing difficulty in consuming certain food due to allergy. This has an adverse effect on the quality of life amongst food allergy sufferers. Medical bills are increased when food allergy sufferers become unknowingly exposed to food allergen. Hence, this study investigated food allergens among food allergy sufferers in order to make their lives better. A total of 250 respondents participated in an online survey. Surprisingly, apart from chicken, soybean and other food allergens that have been listed under the Big Eight Allergens, the respondents mentioned some fruits that could trigger allergic reactions, such as rambutans and watermelons. Food allergy sufferers can be allergic to seafood and seafood products as well, such as shrimp paste or locally known as belacan, which refers to fermented shrimp paste cured under the sun. It is a common food ingredient used among Malaysians. The study findings offer practical insights, such as avoidance of food allergens amidst food allergy sufferers and help the government to carefully manage for menu planning. The knowledge contribution of this study reveals several specific food and fruits, as aforementioned, which appear to be common and nutritious food, yet harmful to food allergy sufferers.